جستجوی استاد راهنمای دانشگاهی

Noela Müllerمشاهده پروفایل

استادیار

• Probability Theory
• Random Matrices
• Sparse Matrices
• +۵ مورد دیگر

Noela Müller is an Assistant Professor in the Mathematics and Computer Science school at Eindhoven University of Technology . Her research focuses on Probability Theory , Random Matrices , and Random Graphs , with significant contributions to understanding the rank of sparse matrices and clique factors in probabilistic settings. Research Outputs : Published 22 works including journal articles and preprints. Collaborations : Active in international networks, particularly in sparse matrix analysis and probabilistic combinatorics. Her recent work explores sparse pooled data algorithms , random 2-SAT models , and sharp thresholds in random graphs , showcasing interdisciplinary applications in computer science, mathematics, and theoretical physics.

• High-dimensional probability theory
• Data Science
• Machine Learning
• +۵ مورد دیگر

Sjoerd Dirksen is a Professor of Mathematics for Data Sciences at Utrecht University since May 2025, having previously served as an Associate Professor for Applied Mathematics (2019-2025) and Junior Professor at RWTH Aachen University (2014-2019). He is affiliated with the Mathematical Institute within the Faculty of Science at Utrecht University, where his office is located in the Hans Freudenthal Building. His research interests focus on high-dimensional probability theory and its applications in data science, machine learning, and signal processing. Specifically, he investigates randomized data dimension reduction methods using structured random matrices, theory for deep learning including random neural networks, high-dimensional covariance estimation for wireless communication systems, and statistical postprocessing of weather forecasts in collaboration with the Royal Netherlands Meteorological Institute (KNMI). Previously, he worked on compressed sensing, sharp estimates for stochastic processes in Banach spaces, and noncommutative analysis. Analysis of his recent publications (2018-2024) reveals a strong focus on quantization effects in high-dimensional data processing, particularly one-bit compressed sensing and covariance estimation under coarse quantization. His work bridges theoretical mathematics with practical applications in signal processing, wireless communications, and meteorological forecasting, demonstrating a consistent trajectory from foundational mathematical research to applied data science problems. Dirksen's academic career shows progression from postdoctoral work at the Hausdorff Center for Mathematics in Bonn to independent research positions. His publication record demonstrates significant contributions to the mathematics of data science, with papers appearing in top journals across mathematics, statistics, and signal processing. His research combines deep theoretical insights with practical applications, particularly in the areas of dimensionality reduction and high-dimensional statistics.

• Extreme Value Theory
• Graphical Models
• Multivariate Statistics
• +۳ مورد دیگر

Frank Röttger is an Assistant Professor at Eindhoven University of Technology, specializing in Mathematical Statistics. His primary research focuses on graphical models, multivariate extremes, and statistical inference in high-dimensional settings. Research Interests : Extreme value theory, probabilistic graphical models, causal inference in extremes, and data-driven risk modeling. Awards : NWO Prize (Scientific) - 2024 Organized Activities : Eurandom Workshop on Graph Laplacians, Multivariate Extremes, and Algebraic Statistics (2024) Causality in Extremes Workshop (2024) Courses Taught : Dependence Modeling Foundations of Statistics Mathematical Statistics Contact : Email: f.rottger@tue.nl

• Statistics
• Machine Learning
• Statistical Genetics
• +۳ مورد دیگر

Dr. Vahe Avagyan is an Assistant Professor at the Mathematical and Statistical Methods - Biometris PE&RC group within Wageningen University & Research. His expertise focuses on advanced statistical methodologies for high-dimensional data analysis, with applications spanning genetics, environmental science, and finance. Key Research Areas: Precision matrix estimation, robust statistical methods, and penalized regression techniques. Applications: Genetic prediction models, carbon emissions analysis, metabolomics, and financial risk management. Recent research emphasizes computational efficiency in genomic prediction models (GxE interactions) and innovative approaches to handling data contamination in covariance estimation. His work combines theoretical rigor with practical implementations, including app-based data collection for urban sustainability studies. Collaborations include researchers from Wageningen University, University of Ghent, and financial institutions, reflecting interdisciplinary applications of his statistical frameworks.

Remco van der Hofstadمشاهده پروفایل

استاد

• Probability Theory
• Statistics
• Complex Networks
• +۶ مورد دیگر

Remco van der Hofstad is a Full Professor and chair of probability at the Department of Mathematics and Computer Science, Eindhoven University of Technology (TU/e). He also serves as scientific director of EURANDOM and co-applicant of the Gravitation program NETWORKS. His research spans probability theory, statistics, and their applications in complex networks, statistical physics, and medical imaging. PhD from University of Utrecht (1997) Positions at McMaster University, Delft TU/e, and TU/e His research focuses on probability questions related to complex networks, including percolation, random graphs, self-interacting processes, and interdisciplinary applications in electrical engineering, computer science, and theoretical physics. Recent work includes medical imaging for glioma patients and theoretical advancements in PageRank analysis, sparse matrices, and dynamic intersection graphs. Key awards include the Prix Henri Poincaré (2003), Rollo Davidson Prize (2007), and Netherlands Organisation for Scientific Research (NWO) VIDI (2003) and VICI (2008) grants. He is editor-in-chief of the Network Pages and acts as spokesman for Platform Wiskunde Nederland. Teaches courses: Probability theory, Probability and Modeling, Probability and Statistics Ancillary activities: Chair of Applied Probability Trust, member of Dutch Chamber of NetSci, KNAW councils

Remco W. van der Hofstadمشاهده پروفایل

استاد

• Probability theory
• Statistics
• Complex networks
• +۷ مورد دیگر

Remco W. van der Hofstad is a Full Professor and Chair of Probability at the Department of Mathematics and Computer Science, Eindhoven University of Technology (TU/e). He also serves as Scientific Director of EURANDOM (Dutch center for statistics, probability theory, and stochastic operations research) and co-directs the 'Random Spatial Structures' program at EURANDOM. His research focuses on probability theory, statistics, and their applications to complex networks including social media systems, with specific interests in percolation, random graphs, self-interacting random processes, and interdisciplinary applications in electrical engineering, computer science, and theoretical physics. Key Affiliations: Eindhoven University of Technology (TU/e) EURANDOM Gravitation Program NETWORKS Platform Wiskunde Nederland (spokesman) Research Highlights: He investigates probabilistic models for complex networks, combining theoretical mathematics with real-world applications. His work connects statistical physics concepts (e.g., percolation theory) with network science challenges in areas like glioma patient neuroimaging and pandemic transmission modeling. Scientific Recognition: Recipient of prestigious awards including the Prix Henri Poincaré (2003), Rollo Davidson Prize (2007), and NWO VIDI/VICI grants. His research contributes to UN Sustainable Development Goals related to scientific innovation. Collaborative Leadership: Active in interdisciplinary projects like the Gravitation Program NETWORKS and the Dutch Mathematics Platform. He also contributes to public dissemination through roles as Editor-in-Chief of the Network Pages community website.